Here’s some interesting insight into the study patterns of students and how Lockdown doesn’t seem to be having any affect at all so far this year……
Here’s my blog hits since August 2020….
NB – despite an increase in traffic this year (which is nice) the pattern you see below has been exactly the same for the last few years….
There is a dip in August, over the summer holiday, but a slow build up in early September – I guess as schools but not colleges start earlier, and then we have a stable weekly trend from September through to mid December, except for a dip when half term week comes – NB there is always a slow down on that last week before half term too.
There’s a significant dip during the XMAS holidays, but that’s to be expected, and then straight back up into January, and not how the half term dip repeats itself.
The final pink line is this week’s already only up to Tuesday, so looks like a bumper week – probably teachers threatening tests on the return in a couple of weeks.
Here’s the daily trend for the last month – you can see the weekend tail off too, every week, and then the half term dip at the end, and finally Monday – first day back after half term.
There will be some differences later this year I think….
There’s no formal exams, probably to be replaced by in house tests which will be earlier than the usual exams I imagine, so I’m not anticipating the usual May-June insane peak in views, I imagine it will be less intense and more spread out as the dates of tests will vary slightly from institution to instiution.
Still, up until now, students are very much creatures of habit. Perhaps Positivists had a point? People really are predictable!
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According to this New York Times heat map, Covid-19 cases seem to be much more prevalent per capita in developed countries compared to developing countries…
The counts are especially high in America, Europe and South America doesn’t fair too well either.
But the count per capita is much lower in Sub-Saharan Africa.
Analysis from Brookings (source) shows the contrast much more starkly – People in developing countries make up 50% of the world’s population but account for only 2% of covid deaths.
The infographic below shows how many people die from covid (the circle) compared to the other main causes of death – if you look at the left hand side, they are generally poorer countries, on the right, generally richer countries…
Are there really fewer covid cases and deaths in poorer countries?
Brookings suggests the different may not be as great as the statistics above suggest. Because….
The different age profiles – Covid-19 affects the very old more severely – especially the over 70s – and to put it bluntly there are hardly any people aged over 70 in poorer countries, because of the lower life expectancy, whereas in developed countries have a more older age profile.
Differences in detecting and reporting covid-19 as a cause of death. In developed countries we have much better detection capacity and it’s possible that Covid has been mis-recorded as a cause of death when really, because of co-morbidity, something else was really the cause. While in the developing world people may well be dying of (or with) covid-19 but it hasn’t been traced.
in short, remember that these covid-19 death statistics are a total social construction.
However, the statics may lack validity, but government responses the world over have been severe – and this social reaction has had very real negative consequences in rich and poor countries alike!
Relevance to A-level sociology
This material is mainly relevant to the global development health topic, but there are also some nice links here to the problems with official statistics.
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Is the world becoming a better place to live? What do the latest trends in global development suggest?
How much progress has been made towards global development since the year 2000?
In this post I examine the global trends in development since the year 2000 according to key statistics from the World Bank, United Nations and other global institutions to try and answer the question: ‘do we live in a better world at the end of 2020 compared to 20 years ago?
I aim to produce a post like this every two years, to keep abreast of the latest trends in Development.
Global Statistics
In this post I am focusing on whole world trends, or truly global statistics, so the very highest level of generalisation to provide an overview, in what you might call the Positivist tradition!
However, at the end of 2020 it is especially difficult to make judgements about the extent of development because of the impact of Coronavirus – we simply don’t know what the medium to long term consequences of this will be on global development.
The chances are that Coronavirus will impact the future development of regions, countries and communities within countries in very different ways, so now more than ever it will be important for students to try to qualify any generalisations about development suggested by the global statistics I am looking at below.
Key Indicators of Development
There is considerable debate over what the most valid indicators of development are, because definitions of ‘development’ vary widely. For this reason I include below several indicators of development, including:
The Human Development Index
Gross National Income (GNI) per capita
Extreme poverty statistics (those living on less than $1.90 a day)
National debt as a proportion of GNI
The employment ratio (the proportion of working age adults in employment)
Life Expectancy
The infant mortality rate
The adult literacy rate
Access to electricity
Peacefulness as measured by the Global Peace Index.
If you want to find out more about exactly what these indicators measure and some of their strengths and limitations you might like to read the following posts:
You can also find further information on some of the specific indicators by following some of the links from my Global Development Page.
Mixed Evidence of Global Development taking place since 2020
Some of the global indicators below suggest there has been significant economic and global development over the last 20 years, other indicators suggest there are significant challenges still facing us as a global population!
For example, the number of people living in extreme poverty has shrunk from nearly 30% of the population to less than 10% while Life Expectancy of females has increased from.
HOWEVER, these are just the global average statistics, and what you need to remember is that the averages will hide variations by country, and variations within countries. The later is especially important to consider – there are regions within some rapidly developing countries that are getting left behind. China and America are two good examples of this.
Some indicators suggest negative trends in development – such as increasing unemployment and increasing violence in some countries, and progress towards sustainable development seems slow.
The Human Development Index
The United Nations Development Programme’s (UNDP) Human Development Index combines Gross National Income, Life Expectancy and Years of Education into one score.
Practically every country shows positive development having taken place since 1990, when HDI first started tracking.
The two countries with significant declines are Syria and Yemen, which have both unfortunately experienced serious conflicts in recent years.
The percentage of the world population living in extreme poverty (as defined by those living on less than $1.90 a day) has decreased from 27.7% to 9.2% from the year 2000 to 2017.
The total external debt of the 120 low- and middle-income countries was $8.1 trillion at the end of 2019, equivalent to 26% of their Gross National Incomes.
Nearly 40 (1/3rd of) low- and middle-income countries had debts greater than 60% of their GNI, treble the amount which had such ratios in 2010.
About 10 low to middle income countries (9%) had debts exceeding 100% of their GNI, 30% up from the number of countries in 2010.
Depending on what you think the role of debt is in development, this could be seen as counter trend to development. Dependency theorists would certainly see the increasing debt levels of poorer countries in this way.
The proportion of working age adults (15+) in paid employment has declined from 61% in 2000 to 57% in 2020.
This seems to be a counter-trend to development, with what is effectively a 4% increase in unemployment over the last 20 years.
However, this does not take into account the fact that more 16-24 year olds may be in education for longer, increasing wages, the impact of huge numbers of women entering the labour market, or the billions of people who are subsistence workers or work informally, so this indicator is an especially challenging one to interpret in terms of what it tells us about development!
The life expectancy of females at birth has increased from 69 years on average in 2020 to 74 years on average in 2018
The fact that women now live 15 years longer on average certainly seems to be one of the most obviously positive indicators of development, going hand in hand with increasing gender equality.
There has been radical progress made in improving the infant mortality rate over the last 20 years – it has reduced from 52.8 per thousand (0.5%) to 28.2 per thousand births (just under 0.3%).
However, the global average is brought down by the higher infant mortality rates in less developed countries, and there is significant room for improvement – in the UK and similarly developed countries, the Infant Mortality rate is only 5 per thousand (0.05%)!
The overall adult literacy rate (of both males and females) has increased from 80% in the year 2000 to 86% in 2020.
6% may not sound like much of an increase, but there is something of a generational factor at work here. One imagines that someone that was 40 in the year 2000 is probably not that likely to become literate by the time they are 60, which is going to be a lag on improving the numbers of people who can read and write.
Most of the improvement above will be due to the increasing numbers of children being taught to read and write at a young age, who then carry this through to adulthood.
There has been relatively rapid progress towards getting more people access to electricity. In the year 2000 only 78% of the world’s population had access, by 2018 that had increased to nearly 90%.
That is an impressive gain from an already high base of 78%!
Carbon Dioxide Emissions are responsible for global warming and corresponding environmental instability and decline, which undermines all other aspects of development.
Sustainable Development only really became a main focus of development from the year 2000, and there seems to have been good progress recently on halting the increase of CO2 emissions:
However, there are many analysts who say that we need to decrease CO2 emissions rather than just hold them level.
Overall the world has become less peaceful since 2009, when Vision of Humanity first started its Global Peace Index.
Today there are 38 countries which are recored as having low to very low levels of peacefulness.
Trends in peacefulness are diverging (becoming further apart) – generally speaking those countries which were more peaceful in 2009 have become even more peaceful (mostly those in Europe), while those which were less peaceful have become even less peaceful (mainly in subsaharan Africa)
While many of the classic indicators of development such as GNI, health and education show signs of positive development, there are clearly challenges remaining – mainly around how to attain better employment levels, and the very serious problems of increasing conflict and how to develop sustainably.
Now they’ve had a day to do some basic analysis of the Scottish exam results the newspapers have had a chance to put their spin on the story – and the narrative runs something like this:
First narrative – ‘Scottish pupils have had their teacher predicted grades lowered by the qualifications authority’.
Second narrative: – Poor Scottish pupils have had their teacher predicted grades lowered more than rich pupils.
Sources
Links to both the above are at the end of this article
This makes for a great story, but I think they might be misleading. As far as I can see, this year’s National Five Scottish students have done better than they would, on average, had they sat the exams.
If you compare the previous years’ results with the teacher predicted grades you get to see how exaggerated those predictions were…..
A comparison of previous year’s results with teacher predicted grades and the actual downward-adjusted grades
All of the data above is from the articles linked below – NB the blue column for the least and most deprived clusters is only 2019 data, A-C pass rate, and the exam results I’m looking are the National 5s, equivalent to the English GCSE.
What’s really going on?
Teachers in Scotland grossly inflated the predicted grades of their pupils, by 10% compared to previous years on average.
They exaggerated the results of the poorest students more than for rich students (bloody left-wing teachers that is!)
The exam authorities modified the results downards, but the results received are still much better than the previous years, showing an improvement.
The poorest students have improved dramatically.
Analysis
It’s highly unlikely that this bunch of students is hyper-successful compared to previous years, so thus unlikely we would have seen an increase in 10% points in the pass rate.
I think the real thing to keep in mind here is what really goes on in exams – pupils sit them, they are marked, and then stats magic is done on them so we end up with a similar amount of passes and grades distribution to the previous years – so it’s hard-wired into exams that little is going to change year on year.
That’s what we’re seeing here – the exam board adjusting to fit the results in with business as usual, but they’ve had to compromise with those optimistic teachers trying to game the system, and as a result, excuse the pun, this year’s Scottish students have done very well, especiallly the poor.
The students who should be angry are last year’s – they’ve lost out relative to this years, next year’s probably too, and those poor mugs actually had to sit their exams, and didn’t get four months off school!
This probably won’t be the way it’s spun in the media – it’s easy enough to find a few students a parents with individual axes to grind, against the overall trend of the 2020 cohort doing very nicely, thank you teachers!
The relationship between social class and educational achievement is one of the main topics within the sociology of education at A level.
The problem is, the government does not routinely collect statistics on the relationship between social class and educational achievement!
Instead, we have to reply on statistics which look at the relationship between household income and educational achievement, rather than the relationship between social class and educational achievement.
Household income is related to social class, but income alone does not tell us exactly which social class someone is from. Some parents might work in traditionally ‘working-class’ jobs which could be very well paid, such as the building trades; while other parents might be earning a limited amount of money working part-time in traditionally middle-class jobs – as private music teachers for example.
Also, income does not necessarily tell us about the cultural aspects of class – how well educated parents are or how much social and cultural capital they have, for example.
Thus you must remember that household income indicators are only proxies for social class, they may not show us precisely what a child’s social class background is.
Two sources we might use to to examine the relationship between social class and educational achievement are:
Free School Meal (FSM) achievement rates compare to non FSM achievement rates
Data on independent school results compared to government schools results.
The Achievement of Pupils Eligible for Free School Meals
Three is a 13.7% achievement gap in the ‘attainment 8’ scores of pupils eligible for Free School Meals compared to non-FSM pupils
In 2019 parents in households with a gross annual income of no more than £16190 were entitled to claim for Free School Meals. (Source).
This means that approximately the poorest 1/6th of households are eligible, so the above statistics are comparing the results of children from the poorest 1/6th of households with the richest 5/6ths all lumped into one.
One limitation with the above statistics is that if you were to stretch this comparison out and compare the poorest 1/6th with the next poorest 1/6th and so on up to the riches 1/6th, you would probably see much starker differences.
Independent School Results Compared to State Schools
If we look at the top 10 independent school results compared to the top 10 state schools, we see quite a difference in results.
In order to be able to pay the fees to get your children into an independent school, you have to be comfortably in the top 10% of households. There are a few scholarships for pupils from poorer households, but not in significant numbers!
Top 10 independent schools
Top 10 state schools
You can see a clear 8-9% difference in achievement in favour of the fee-paying independent schools.
One advantage of the above stats is that it’s much more likely that you’re seeing the solidly upper middle class in these schools, rather than this just being about income.
However, we are only talking about the the top 5-10% of the social class scale, we are not able to make social class comparisons more broadly.
Conclusions
If we use the above data, we can see there is a drastic difference in the achievement rates at the very top and the very bottom of the household income scales.
IF we think household income is a valid indicator of social class, we can also say there are huge social class differences in educational achievement based on the above statistics.
However, we don’t have systematic, annual data on the relationship between the vast majority of middle income households and educational achievement.
a look at how GCSE, A-level and degree results vary by ethnic group in England and Wales.
The Department for Education makes it very easy to access statistics on educational achievement. Below I summarise some of the recent trends in educational achievement in England and Wales by ethnicity and offer some commentary on what I think needs explaining, and some thoughts on the limitations of these statistics
Average attainment 8 Score by Ethnic group 2018
Attainment 8 is a way of representing all GCSE results as a single percentage!
The average score for all ethnic groups together was 46.5/90. It’s no surprise to find this is very close to the ‘White British group as White British children still make up the vast majority of school children.
To my mind the headline figures from the above statistics are as follows
White, Pakistani and Black African children have results very close to the national average of 46.5, and Bangladeshi children achieved 3% higher. All of these figures are quite close together and so nothing really needs explaining for these broad groups.
Chinese children achieve 18% higher than the national average
Indian children 10% higher
Black Caribbean children underachieve by about 7% points
Irish Traveler and Gypsy Roma children have the worst underacheivement levels with 18% and 22% respectively.
So what needs explaining from the above is why Chinese and Indian children do so well, and why Black Carribean children underachieve, and why Irish traveler and Gypsy Roma children do so badly.
In terms of impact of research it’s probably worth focusing on Chinese, Indian and Black Caribbean children because there are many more of these than of the last two ethnic groups.
A final point to note about these statistics is that it doesn’t seem useful to lump together ‘Black’ and Asian’ students because there are SIGNIFICANT differences in the achievement rates within these groups.
Educational Achievement (attainment 8) by Free School Meals and Ethnicity
If we look at GCSE results by free school meal eligibility (roughly the poorest sixth of children) we see that ethnicity still has an independent effect on achievement – the pattern is broadly the same as in the chart above, but with the following two differences:
No free school meal children (roughly the wealthiest 5/6ths of children) move closer together slightly.
For the FSM groups, white and mixed children are now the lowest achievers, suggesting that poor white and mixed kids do comparatively worse than poor kids from all other ethnic groups.
NB – I think the DFE here is doing a cunning job of disguising the fact that ‘income’ has a larger affect on results than ethnicity – we are seeing here the poorest 1/6th (FSM) compared to the richest 5/6ths (No FSM). If we were to stretch this out and compare just the poorest 1/6th (which we’ve got) to the richest 1/6th my guess would be that you’d find very similar levels of achievement across what would be the upper middle classes for all ethnic groups.
Statistics on Participation in Further Education
This demonstrates a long standing trend – that ethnic minorities (Black and Asian) students are more likely to carry on into further education compared to white students. This should mean that you’ll see a higher proportion of white kids starting work based apprenticeships.
NB – making comparisons to the overall population is a bit misleading as the age profile for ethnic minorities tends to be younger.
Students achieving at least 3 As at A-level
The overall average is 12.9%.
These are quite interesting.
Huge ‘over-achievement’ by Chinese kids – 22.5%
Indian kids do slightly better than average at 15%
Signficant underachievement for Pakistani and Bangladeshi kids – around 7%
Terrible underachievement for Black African and Caribbean kids at 5.6% and 3.5% respectively.
The source notes that the Irish Traveler population is only 7 people, so one can’t generalize, still, at least it busts a few stereotypes!
These stats show something of an exaggeration of what we saw at GCSE.
I put these stats in the ‘interesting but not that useful’ category – I’d rather see the percentages for high grades or A-C grades to make these a bit more representative.
Degree results by ethnicity
Surprisingly, we see white students gaining significant ground on ethnic minority students with 30.9% of white students gaining a first class degree (*).
Black students in comparison come crashing down to just 14% of first class degrees.
These kind of differences – from similar GCSE results for Black and White students to such different A-level and degree results need further investigation.
(1)The education statistics above form part of the government’s Ethnicity Facts and Figures series, you can check out a wider range of statistical evidence on ethnicity and life chances by clicking here. (As always, remember to be critical of the limitations of these statistics!).
(*) WTF – 30% – sorry kids, but a lot of those first class degrees are probably down to grade inflation, which in turn is probably down to the fact that students are now paying £30 K for yer for their degrees.
189 police officers have been convicted across 12 police forces in England in Wales in five years since 2013 , according to a recent FOI request (source: The Telegraph). This equates to just 37.8 police officer convictions each year.
According to Full Fact, there were 126, 300 total police officers in England and Wales in March 2019.
This gives us a police officer conviction rate of 0.03% per year – that is to say that 0.03% of police officers are convicted of a crime each year.
1.38 million people in the general population were prosecuted in the year (CJS Stats, 2018)
A very rough estimate for the number of adults in England and Wales is around 50 million, so this gives us a rough adult conviction rate of 2.76 per year.
This means the Police officer conviction rate is 100 times less than that for the population as a whole.
How accurate are these statistics?
Personally I’m sceptical about the police officer conviction rate.
Despite the fact that the police probably are less likely to commit crime – I mean it kind of goes with the job, not committing crime, and then there’s the embarrassment of getting caught even if you are criminally inclined, which I imagine would be a further deterrent, I still think there’s a lot of criminal police officers whose crimes are just not getting detected.
I imagine you’d be less likely to be suspected of a crime – I mean the police themselves aren’t going to get stopped and searched are they?
Then there’s the fact that prosecutors might be more reluctant to prosecute police because it makes the system look flawed.
Then of course there’s all those things which won’t be defined as criminal because it’s the police doing them in the line of duty – such as speeding and violence, and drug possession come to think of it.
how useful are different types of data visualization for displaying information about the number of schools in the UK, and how they are changing over time?
I’ve just been experimenting with different ways of visualizing the relative number of different types of school in the UK, and how these school types are changing over time.
The main school types I’ve focused on are:
nurseries
primary
middle (hardly any of these!)
secondary
non-maintained schools
special schools
pupil referral units.
You can view all of my visualizations on my Tableau profile. If you click on any of the images below, they will take you to the live vizes on Tableau.
I think the Tree Map is the best way of providing an overview of the different types of school in the UK. As you can see from the tree map below, there are A LOT more primary schools than secondary schools in the UK, and primary and secondary together (unsurprisingly) account for most of the schools in the UK. In contrast, there are hardly any Pupil Referral Units.
NB – make sure you’ve only got one year box checked, otherwise you get totals of the years checked, which is pointless!
The limitations of the Tree Map Visualization
Although (IMO) this type of viz provides the best ‘frozen in time’ overview, it doesn’t actually allow you to make comparisons across time very easily, because you can only see the distribution for one year at a time.
One could overcome this by having two or more tree maps on display at once, but this still wouldn’t make for easy comparison as the layout of the boxes is likely to change as the data changes. To show changes over time effectively you need different types of visualization:
Changing schools viz 1
This is the most basic type of viz showing changes over time…
Changing schools viz 2
I think viz 2 is much better as the fill gives you a much more immediate impression of how many of each type of school there is.
Changing schools viz 3
Given the relatively small amount of data for this particular viz I think this works quite nicely too, gives you a bit more of a sense of the relative numbers and much better for highlighting smaller numbers…
How useful are these visualizations?
As they stand they only show us a very general level of information, with no granularity. All of these vizes could be much more useful if you could ‘drill down’ into the data to see how the stats vary by England, Wales and Scotland.
Also, these have been designed as only the first stage in a story which also focus in on pupil numbers in different school types (also in relation to pupil types – male/ female etc.), and teacher numbers and teacher-student ratios.
What can prison population statistics tell us about Crime Control in the UK? Is Prison an effective strategy for controlling crime?
These are questions that should be of interest to any student studying the Crime and Deviance option within A-level sociology.
Scotland, England and Wales have high prison populations
In England and Wales we lock up 40% more people than in France and almost twice as many people as they do in Germany, which are broadly comparable countries.
Yet there is no link between the prison population and levels of crime
England and wales have seen a rising prison population and a rising then a rapidly falling crime rate
Finland has seen a declining prison population and a rising and then a gradually declining crime rate.
Canada has seen a broadly level prison population and yet a relatively stable crime rate.
Most people are serving short sentences for non-violent offences
Nearly 70% of the prison population are in for non-violent offences – which means that 30% are in for violent offences. In those prisons where the two populations are mixed, this must be awful for some of those non-violent offenders.
People are getting sentenced for longer
I’m not sure what’s underlying this rise in more serious offences …. the most obvious long-sentence crime of murder has decreased in recent years, so maybe this is for violent gang related and terrorist related crimes which involve in harm rather than death ? Something to research further!
Does Prison work?
In short, if controlling crime is what you hope to achieve, then no it doesn’t because nearly 50% of those sent to prison are recalled within 1 year of being released.
However, there are more reasons why you might want to lock people up other than just rehabilitating them and preventing future offending – there is an argument that they just deserve to be punished whether they reoffend or not.
How do community service orders and suspended sentences compare to prison?
it seems that both of these are more effective at preventing reoffending, but the difference isn’t that great:
63% of people who serve sentences of less than 12 months reoffend compared to
56% of those who receive community orders and compared to
54% of those who receive suspended sentences.
HOWEVER, this may be due to the fact that those avoiding jail have different circumstances and/ or different characters to those who do go to jail – they might just be the kinds of people less likely to reoffend already!
Conclusions
Overall these prison statistics suggest that while we like to lock people up in England and Wales, there is little evidence that doing so prevents crime.
Maybe we should be looking for cheaper and more effective solutions – such as early intervention (initially expensive but cheaper than several years in and out of jail), or public shaming for example?
The easy answer is to say around 22% of the population, roughly 14 million people. The long answer starts with the sentence ‘it depends on how you define and measure poverty’, in which case you get various different statistics on the poverty rate.
Statistics on poverty in the UK
According to the Social Metrics Foundation, which seems to be endorsed by the Joseph Rowntree Foundation….
22% of the UK population are in poverty, equivalent to 14.2 million people: 8.4 million working-age adults; 4.5 million children; and 1.4 million pension age adults. Source: The Social Metrics Foundation, 2018.
1% of the total UK population (7. 7 million people) live in persistent poverty. Source: The Social Metrics Foundation, 2018.
This definition of poverty is broader than any previous definition because:
It takes account of all material resources not just incomes. For instance, this means including an assessment of the available assets that families have; •
It takes into accounts the inescapable costs that some families face, which make them more likely than others to experience poverty, such as the extra costs of disability, and costs of childcare and rental and mortgage costs; •
It automatically defines anyone who is ‘sleeping rough’ as being in poverty.
However, it also sets the relative poverty line at 55% of median income rather than 60^ of median income (as the government has done for many years), seemingly because to keep it at 60% while making all of the other changes above would put too many people in poverty?!? See page 63 of the report for more details:
According to the Government’s own data:
16% of UK households were in relative low income households (before housing costs)
22% of UK households were in relative low income households (after housing costs).
Relative low income households have an income of less than 60% of median household income (equivalised), which is equivalent to £296 per week (or approximately £1000 per month). Source: Households Below Average Income, published March 2018.
7.3% of the UK population (4.6 million people) are in persistent poverty. This study defines ‘persistent poverty as being in a relative low income household (using the BHAI definition of this) consistently for 3 years. Source: Persistent Poverty in the UK and the EU: 2015.
Which of these is the most valid measurement of poverty?
You’ll notice that there’s some different between these figures, especially between the Social Metric Commissions’ persistent poverty rate and the ONS’ poverty rate – 12% compared to 7%, so it really matters which of these is the most valid!
Given that the Social Metrics Commission’s definition was agreed by a large panel of people, which included government representation, I’m going to say the SMC’s definition/ measurement is the most valid.
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